NVIDIA Tests Three Lower-Memory Rubin Ultra Variants to Mitigate HBM Supply Shortages

NVIDIA evaluates reduced HBM configs for Rubin Ultra, testing three low-memory versions. This shift aims to ease production bottlenecks but may raise deployment costs for major cloud providers.

Woofun AI reports that NVIDIA is adjusting the High Bandwidth Memory (HBM) configuration for its next-generation Rubin Ultra AI GPU to address severe supply constraints. The company has tested at least three distinct versions with reduced memory capacities over recent weeks, prioritizing supply availability over original high-specification designs.

This strategic compromise implies that enterprises running large language models may need to deploy additional GPUs, potentially increasing system costs and cluster complexity for major cloud providers like Microsoft, Meta, Amazon, and Google. The move underscores persistent HBM bottlenecks, as production capacity from key suppliers SK Hynix and Micron remains tight despite NVIDIA’s dominant market position.